“…Early methods based on inverse optimal control also use hand-crafted cost features, and learn linear weighting functions to rationalize trajectories which are assumed to be generated by optimal control [18]. Recent data-driven approaches based on deep networks [1,4,9,10,13,19,20,24,28,29,31] outperform traditional approaches. Most of this work focuses either on modeling constraints from the scene context [29] or on modeling social interactions among multiple agents [1,9,10,13,31]; a smaller fraction of work considers both aspects [4,20,28].…”